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Don't just predict
the number.
Change it.

Most analytics tools stop at "here's what happened" or "here's what will happen." ORM goes further. We tell you exactly what to do about it. Specific actions. Prioritized by impact. Delivered every week.

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The Four Levels

Most revenue teams are stuck
at level two.

There are four levels of analytics maturity. Most B2B SaaS companies only use the first two. Understanding the difference is the key to understanding why your current tools feel like they are not working.

Descriptive: What happened?

This is your CRM reporting. Dashboards. Charts. Last quarter you closed $7.1M. Win rate was 22%. Average sales cycle was 68 days. Descriptive analytics tells you the score after the game is over. Useful for board decks. Not useful for changing the outcome.

Diagnostic: Why did it happen?

This is where most "revenue intelligence" platforms live. They help you slice the data. Win rate dropped because enterprise deals stalled. Pipeline coverage was thin in the West region. The diagnostic layer explains the past. It still does not tell you what to do next.

Predictive: What will happen?

Forecasting tools live here. They take your current pipeline and project an outcome. "Based on your current pipeline, you will likely close $6.8M this quarter." Better than descriptive. But a prediction without a plan is just a more sophisticated way to worry.

Prescriptive: What should we do?

This is where ORM operates. Prescriptive analytics takes the prediction and converts it into specific actions. Not "improve pipeline coverage." Instead: "Add $1.4M in pipeline from the financial services segment, where your win rate is 31% versus 18% in healthcare. Accelerate the Acme deal by scheduling the technical review this week. Shift two mid-market reps to cover the open territory in the Southeast."

The difference between "you will miss your number" and "here is exactly what to change to hit it."

In Practice

What prescriptive analytics
actually looks like.

Deal Prioritization

Your reps have 40+ deals in flight. They cannot give equal attention to all of them. ORM's model scores every deal by likelihood to close and revenue impact, then tells your team exactly which deals to focus on this week. Not a dashboard to sort through. A ranked list with reasons.

DEAL PRIORITY QUEUE 1 Acme Corp Stage 4 | $180K | 87% close probability Schedule tech review 2 TechFlow Inc Stage 3 | $95K | 64% close probability Send case study 3 DataBridge Stage 3 | $220K | 52% close probability Engage champion 12 more deals ranked below

Pipeline Gap Analysis

You are $2.1M short of target. ORM does not just tell you that. It tells you where to find the pipeline. Which segments have the highest conversion rates. Which deal sources produce the fastest closes. Where your team should spend the next two weeks prospecting.

PIPELINE GAP PRESCRIPTION Gap to target $2.1M short of $8.2M target +$900K Financial Services Win rate: 31% | Avg cycle: 52d +$720K Expansion Deals Win rate: 44% | Avg cycle: 28d +$480K Mid-Market New Business (Southeast) Open territory | 4 reps under-allocated

Resource Optimization

Should you hire two more reps or reallocate the ones you have? ORM models both scenarios using your actual ramp rates and territory data. You get a specific answer with projected revenue impact, not a "it depends" recommendation.

RESOURCE SCENARIOS OPTIMAL Reallocate + 1 hire $1.6M incremental revenue | 3.2x ROI +$1.6M Hire 2 reps, no reallocation $1.1M incremental | 1.8x ROI | 4.5mo ramp +$1.1M Status quo Miss target by $2.1M -$2.1M

Weekly Action Plans

Every week, ORM delivers a set of specific actions tied to your forecast. Not a report to interpret. A plan to execute. Which deals need attention. Where the pipeline is soft. What your team should focus on for the next seven days.

WEEKLY ACTION PLAN — WK 6 Accelerate 3 Stage 4 deals (combined $420K) Add 5 qualified opps in financial services Schedule QBR with top 2 expansion accounts Clean 8 stale opportunities from pipeline
The ORM Difference

Prescriptive analytics
requires custom models.

Here is the thing about prescriptive analytics. You cannot deliver meaningful prescriptions from a generic model. If the model does not understand your specific sales cycle, your conversion patterns by segment, and your team's actual capacity, the recommendations will be generic too. "Improve pipeline coverage" is not prescriptive. It is a platitude.

That is why ORM builds every model from scratch on your CRM data. The prescriptions are specific because the model is specific. It knows that your financial services deals close 40% faster than healthcare. It knows that deals sourced from events have a 2x higher win rate than outbound. It knows which reps are strongest in which segments.

The result is not a dashboard you stare at. It is a weekly set of actions your team can execute immediately. Move this deal forward. Prospect in this segment. Reallocate this territory. Each action is tied to a specific revenue impact.

To go deeper on the concept, see our glossary entry on prescriptive analytics. For the full picture of how this fits into a forecasting workflow, read our complete guide to sales forecasting. And if you want to see how ORM's prescriptive approach compares to platform-based tools, visit Optimized Sales.

From data to action in three steps.

ORM connects to your CRM, builds a custom model, and delivers prescriptive actions every week.

Connect1

ORM reads your CRM data. No migration, no integration project, no workflow changes for your team.

Model2

We build a custom model calibrated to your sales motion, segments, and conversion patterns. 4-6 weeks to full calibration.

Prescribe3

Weekly forecasts and specific actions delivered to your team. What to focus on, where to add pipeline, which deals to accelerate.

Frequently asked questions

Concept
What is prescriptive analytics?+
Prescriptive analytics goes beyond telling you what happened (descriptive) or what will happen (predictive). It tells you what to do about it. Specific actions, prioritized by impact, that your team can execute.
How is prescriptive analytics different from predictive?+
Predictive analytics forecasts outcomes. Prescriptive analytics recommends actions. A predictive model says you will close $7.2M this quarter. A prescriptive model says accelerate these 4 deals, add pipeline in this segment, and reassign this territory to hit $8.5M.
ORM
Does ORM provide prescriptive analytics for sales teams?+
Yes. ORM builds custom prescriptive models on your CRM data that deliver specific, actionable recommendations for your revenue team every week. Not dashboards. Actions.
What are examples of prescriptive analytics in B2B sales?+
Prescriptive analytics in B2B sales includes recommendations like: which deals to prioritize this week, where to add pipeline by segment, which reps need coaching on specific deal types, and how to reallocate resources to close the gap to target.

Stop analyzing. Start acting.

See what prescriptive analytics looks like when it is built on your data.

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